Bart Bakker

Publication Activity (10 Years)

Years Active: 1999-2021
Publications (10 Years): 7

Top Topics

Anomalous Behavior

Unsupervised Learning

Anomaly Detection

Training And Test Data

Top Venues

Publications

Patricia M. Johnson, Geunu Jeong, Kerstin Hammernik, Jo Schlemper, Chen Qin, Jinming Duan, Daniel Rueckert, Jingu Lee, Nicola Pezzotti, Elwin de Weerdt, Sahar Yousefi, Mohamed S. Elmahdy, Jeroen Hendrikus Franciscus Van Gemert, Christophe Schülke, Mariya Doneva, Tim Nielsen, Sergey Kastryulin, Boudewijn P. F. Lelieveldt, Matthias J. P. van Osch, Marius Staring, Eric Z. Chen, Puyang Wang, Xiao Chen, Terrence Chen, Vishal M. Patel, Shanhui Sun, Hyungseob Shin, Yohan Jun, Taejoon Eo, Sewon Kim, Taeseong Kim, Dosik Hwang, Patrick Putzky, Dimitrios Karkalousos, Jonas Teuwen, Nikita Miriakov, Bart Bakker, Matthan W. A. Caan, Max Welling, Matthew J. Muckley, Florian Knoll
Evaluation of the Robustness of Learned MR Image Reconstruction to Systematic Deviations Between Training and Test Data for the Models from the fastMRI Challenge. MLMIR@MICCAI (2021)
Nina Shvetsova, Bart Bakker, Irina Fedulova, Heinrich Schulz, Dmitry V. Dylov
Anomaly Detection in Medical Imaging With Deep Perceptual Autoencoders. IEEE Access 9 (2021)
Nina Tuluptceva, Bart Bakker, Irina Fedulova, Heinrich Schulz, Dmitry V. Dylov
Anomaly Detection with Deep Perceptual Autoencoders. CoRR (2020)
Nina Tuluptceva, Bart Bakker, Irina Fedulova, Anton Konushin
Perceptual Image Anomaly Detection. CoRR (2019)
Patrick Putzky, Dimitrios Karkalousos, Jonas Teuwen, Nikita Miriakov, Bart Bakker, Matthan W. A. Caan, Max Welling
i-RIM applied to the fastMRI challenge. CoRR (2019)
Nina Tuluptceva, Bart Bakker, Irina Fedulova, Anton Konushin
Perceptual Image Anomaly Detection. ACPR (1) (2019)
Suzanne C. Wetstein, Allison M. Onken, Christina Luffman, Gabrielle M. Baker, Michael E. Pyle, Kevin H. Kensler, Ying Liu, Bart Bakker, Ruud Vlutters, Marinus B. van Leeuwen, Laura C. Collins, Stuart J. Schnitt, Josien P. W. Pluim, Rulla M. Tamimi, Yujing J. Heng, Mitko Veta
Deep learning assessment of breast terminal duct lobular unit involution: towards automated prediction of breast cancer risk. CoRR (2019)
Pieter Horn, Bart Bakker, Gijs Geleijnse, Jan H. M. Korst, Sergei Kurkin
Determining causal and non-causal relationships in biomedical text by classifying verbs using a Naive Bayesian Classifier. BioNLP (2008)
Bart Bakker, Tom Heskes
Learning and approximate inference in dynamic hierarchical models. Comput. Stat. Data Anal. 52 (2) (2007)
Hauke Schramm, Xavier L. Aubert, Bart Bakker, Carsten Meyer, Hermann Ney
Modeling spontaneous speech variability in professional dictation. Speech Commun. 48 (5) (2006)
Bart Bakker, Carsten Meyer, Xavier L. Aubert
Fast unsupervised speaker adaptation through a discriminative eigen-MLLR algorithm. INTERSPEECH (2005)
Bart Bakker, Tom Heskes
Task Clustering and Gating for Bayesian Multitask Learning. J. Mach. Learn. Res. 4 (2003)
Bart Bakker, Tom Heskes
Clustering ensembles of neural network models. Neural Networks 16 (2) (2003)
Tom Heskes, Jan-Joost Spanjers, Bart Bakker, Wim Wiegerinck
Optimising newspaper sales using neural-Bayesian technology. Neural Comput. Appl. 12 (3-4) (2003)
Tom Heskes, Bart Bakker, Bert Kappen
Approximate algorithms for neural-Bayesian approaches. Theor. Comput. Sci. 287 (1) (2002)
Bart Bakker, Tom Heskes
Model Clustering for Neural Network Ensembles. ICANN (2002)
Bart Bakker, Tom Heskes
Model clustering by deterministic annealing. ESANN (1999)